1. Field of the Invention
The present invention is directed generally to methods of analyzing plaques formed in arterial walls of coronary arteries.
2. Description of the Related Art
All publications herein are incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. The following description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
Each year, one million people in the United States and nineteen million people worldwide experience a sudden acute coronary event (sudden cardiac death or myocardial infarction). See Yusuf S., Reddy S., Ounpuu S., Anand S., Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization, Circulation, 2001; 104(22):2746-53. Early detection and accurate assessment of coronary artery disease is crucial in the identification of patients at risk of these highly common yet usually preventable coronary events.
Although the current standard for assessing coronary artery disease is the identification of anatomically significant coronary luminal stenosis by invasive coronary angiography, it is known that most acute coronary syndromes arise from plaques that are not critically occlusive. See Falk E., Fuster V., Angina pectoris and disease progression, Circulation, 1995; 92(8):2033-5, and Virmani R., Burke A. P., Farb A., Kolodgie F. D., Pathology of the vulnerable plaque, J. Am. Coll. Cardiol., 2006; 47 (8 Suppl):C13-8. Histopathologic analyses have shown that the “vulnerable” plaques considered responsible for acute coronary events have a large lipid pool, a thin cap, and macrophage-dense inflammation on or beneath their surfaces. See Virmani R., Kolodgie F. D., Burke A. P., Farb A., Schwartz S. M., Lessons from sudden coronary death: a comprehensive morphological classification scheme for atherosclerotic lesions, Arterioscler Thromb Vasc Biol., 2000; 20(5):1262-75. This strongly suggests that plaque composition and structure may be associated with future coronary events. See Akram K., Rinehart S., Voros S., Coronary arterial atherosclerotic plaque imaging by contrast-enhanced computed tomography: Fantasy or reality?, J. Nucl. Cardiol., 2008; 15(6):818-29, and Narula J., Finn A. V., Demaria A. N., Picking plaques that pop, J. Am. Coil. Cardiol., 2005; 45(12):1970-3. Therefore, a need exists for methods and systems that determine plaque composition.
Cardiac computed tomography angiography (“CCTA”) is an imaging method that uses a computed tomography (“CT”) scanner to image structures and blood vessels of the heart. CCTA performed using a 64-slice CT scanner has recently become an increasingly effective clinical tool for noninvasive assessment of the coronary arteries and for assessing plaque composition. See Achenbach S., Cardiac CT: state of the art for the detection of coronary arterial stenosis, J. Cardiovasc. Comput. Tomogr., 2007; 1(1):3-20, and Berman D. S., Shaw L. J., Hachamovitch R., Friedman J. D., Dm Polk, Hayes S. W., Thomson L. E., Germano G., Wong N. D., Kang X., Rozanski A., Comparative use of radionuclide stress testing, coronary artery calcium scanning, and noninvasive coronary angiography for diagnostic and prognostic cardiac assessment, Semin. Nucl. Med., 2007; 37(1):2-16. CCTA has also shown substantial potential for in vivo plaque component characterization. See Leber A. W., Becker A., Knez A., von Ziegler F., Sirol M., Nikolaou K., Ohnesorge B., Fayad Z. A., Becker C. R., Riser M., Steinbeck G., Boekstegers P., Accuracy of 64-slice computed tomography to classify and quantify plaque volumes in the proximal coronary system: a comparative study using intravascular ultrasound, J. Am. Coll. Cardiol., 2006; 47(3):672-7; Leber A. W., Knez A., Becker A., Becker C., von Ziegler F., Nikolaou K., Rist C., Reiser M., White C., Steinbeck G., Boekstegers P., Accuracy of multidetector spiral computed tomography in identifying and differentiating the composition of coronary atherosclerotic plaques: a comparative study with intracoronary ultrasound, J. Am. Coll. Cardiol., 2004; 43(7):1241-7; Leber A. W., Knez A., von Ziegler F., Becker A., Nikolaou K., Paul S., Wintersperger B., Reiser M., Becker C. R., Steinbeck G., Boekstegers P., Quantification of obstructive and nonobstructive coronary lesions by 64-slice computed tomography: a comparative study with quantitative coronary angiography and intravascular ultrasound, J. Am. Coll Cardiol., 2005; 46(1):147-54; and Petranovic M., Soni A., Bezzera H., Loureiro R., Sarwar A., Raffel C., Pomerantsev E., Jang I. K., Brady T. J., Achenbach S., Cury R. C., Assessment of nonstenotic coronary lesions by 64-slice multidetector computed tomography in comparison to intravascular ultrasound: evaluation of nonculprit coronary lesions, J. Cardiovasc. Comput. Tomogr., 2009; 3(1):24-31.
A plaque may include non-calcified and/or calcified components. In CCTA scan data, attenuation thresholds may be used to identify structures, such as plaques, and evaluate their compositions. For example, the CCTA scan data may be used to determine whether a plaque contains non-calcified components and/or calcified components. Further, the CCTA scan data may be used to determine the percentage of a plaque this non-calcified versus calcified.
Unfortunately, plaque attenuation thresholds have been shown to vary significantly with intracoronary lumen attenuation and choice of reconstruction kernel. Therefore, plaque attenuation thresholds may vary between patients as well as between scans. In other words, plaque attenuation thresholds are patient and scan specific. See Cademartiri F., Mollet N. R., Runza G., Bruining N., Hamers R., Somers P., Knaapen M., Verheye S., Midiri M., Krestin G. P., de Feyter P. J., Influence of intracoronary attenuation on coronary plaque measurements using multislice computed tomography: observations in an ex vivo model of coronary computed tomography angiography, Eur. Radiol., 2005; 15(7):1426-31; and Cademartiri F., La Grutta L., Runza G., Palumbo A., Maffei E., Mollet N. R., Bartolotta T. V., Somers P., Knaapen M., Verheye S., Midiri M., Hamers R., B ruining N: Influence of convolution filtering on coronary plaque attenuation values: observations in an ex vivo model of multislice computed tomography coronary angiography, Eur. Radiol., 2007; 17(7):1842-9.
Currently, to evaluate plaques in CCTA scan data, the plaques must be identified manually and separated from other structures. In particular, accurate and reproducible measurement of coronary plaque has been limited by the need to manually trace contours separating epicardial fat from the vessel wall. Further, contours enclosing plaque components must also be manually traced. This manual tracing process is time consuming and can be prone to undesirable intra-observer variability. See Burgstahler C., Reimann A., Beck T., Kuettner A., Baumann D., Heuschmid M., Brodoefel H., Claussen C. D., Kopp A. F., Schroeder S., Influence of a lipid-lowering therapy on calcified and noncalcified coronary plaques monitored by multislice detector computed tomography: results of the New Age II Pilot Study, Invest. Radiol., 2007; 42(3):189-95; and Schmid M., Achenbach S., Ropers D., Komatsu S., Ropers U., Daniel W. G., Pflederer T., Assessment of changes in non-calcified atherosclerotic plaque volume in the left main and left anterior descending coronary arteries over time by 64-slice computed tomography, Am. J. Cardiol., 2008; 101(5):579-84.
Another approach used to evaluate plaque composition available in some current commercial implementations allows an operator to manually and interactively determine (or modify) the plaque attenuation thresholds used for each plaque. Like the other manual process mentioned above, establishing the plaque attenuation thresholds manually for each plaque may be time consuming and yield operator dependent results.
Standardized and automated quantification of non-calcified components, calcified components, and total plaque burden from CCTA scan data, although extremely challenging, is of great interest for refinement of cardiovascular risk stratification. See Akram K., Rinehart S., Voros S., Coronary arterial atherosclerotic plaque imaging by contrast-enhanced computed tomography: Fantasy or reality?, J. Nucl. Cardiol., 2008; 15(6):818-29; and Schuijf J. D., Bax J. J., How do you quantify noncalcified plaque?, J. Cardiovasc. Comput. Tomogr., 2008; 2(6):360-5. Although others have developed various methods for quantifying non-calcified plaque imaged by CCTA. See Clouse M. E., Sabir A., Yam C.-S., Yoshimura N., Lin S., Welty F., Martinez-Clark P., Raptopoulos V., Measuring noncalcified coronary atherosclerotic plaque using voxel analysis with MDCT angiography: a pilot clinical study, AJR Am. J. Roentgenol., 2008; 190:1553-60.
Nevertheless, currently available technologies fail to provide a method or system capable of providing standardized and automated quantification of non-calcified and calcified components in clinical CCTA scan data captured by standard multi-slice CCTA scanners. Furthermore, currently available technologies also fail to provide a method or system capable of performing automated CCTA plaque segmentation, a key step toward standardized quantification of non-calcified and calcified components in plaques.
As an example, Clouse et al. supra, describes a “voxel analysis” technique that uses Analyze-Direct software (www.analyzedirect.com; Mayo Clinic, Rochester, Minn.). In this technique, expert readers manually draw eight perpendicular line profiles through a plaque, and attenuation values in eight radial voxels for each line profile are measured. Using these manually defined points, attenuation thresholds for the lumen, epicardial fat, and arterial wall are calculated from interpolation of the line profiles. Then, the lumen and plaque volumes are calculated.
Gertz et al. infra describe using 2D isotropic wavelet analysis to characterize micro-CT images of excised human coronary arteries. Compared with histology, they found that wavelet analysis allowed identification of coronary plaque components with 81% sensitivity and 86% specificity. See Gertz S. D., Bodmann B. G., Vela D., Papadakis M., Aboshady I., Cherukuri P., Alexander S., Kouri D. J., Baid S., Gittens A. A., Gladish G. W., Conyers J. L., Cody D. D., Gavish L., Mazraeshahi R. M., Wilner W. T., Frazier L., Madjid M., Zarrabi A., Lukovenkov S., Ahmed A., Willerson J. T., Casscells S. W., Three-dimensional isotropic wavelets for postacquisitional extraction of latent images of atherosclerotic plaque components from micro-computed tomography of human coronary arteries, Acad. Radiol., 2007; 14(12):1509-19.
Recent in vivo studies comparing manual plaque characterization from 64-slice CCTA to an invasive intravascular standard have found significant overlap between lipid-rich and fibrous non-calcified components and high intra-observer variability. See Leber 2006 supra; and Petranovic et al. supra.
Therefore, as explained above, a need exists for methods and systems capable of performing automated quantification of non-calcified and calcified components of plaques imaged in CCTA scan data. A method or system that provides standardize quantification of these components would be particularly desirable. The present application provides these and other advantages as will be apparent from the following detailed description and accompanying figures.